[{"data":1,"prerenderedAt":94},["ShallowReactive",2],{"seo-verification":3,"marketplace-app-en-whisper":6},{"google":4,"bing":5},"EycwPY2XMyTkVzas3n1ygeNJFGAH513qrMjfDljzsMQ","",{"slug":7,"name":8,"description":9,"phase":10,"unavailableReason":11,"docsUrl":12,"logo":13,"github":13,"tagline":14,"longDescription":15,"features":16,"useCases":23,"steps":33,"faq":49,"specs":65,"compatibleOs":71,"relatedApps":72,"relatedPosts":88,"category":91},"whisper","Whisper","Open-source self-hosted audio transcription API: convert your recordings into timestamped text via REST, with full privacy on your own VPS.",2,"awaiting_qa","https:\u002F\u002Fservorbit.com\u002Fblog\u002Fheberger-whisper-vps",null,"Private speech-to-text API on your VPS — multilingual, fast, OpenAI-compatible.","Whisper is OpenAI's open-source speech recognition model, here deployed as a self-hosted REST API via the faster-whisper CTranslate2 backend. Running on your VPS, it transcribes audio files in 99 languages, translates to English, and returns word-level timestamps — all without sending a single byte to a third-party service. The `base` model runs comfortably on a 1-vCPU VPS with 1 GB of RAM; the `small` model lifts accuracy further with 2 GB. Use it to power captioning, search indexing, meeting notes, podcast processing or any workflow that converts voice to text.",[17,18,19,20,21,22],"OpenAI-compatible REST API: POST \u002Fasr, output as txt, json, srt, vtt or tsv.","faster-whisper CTranslate2 backend: up to 4× faster than original Whisper on CPU.","99 languages supported — Arabic, French, English, Darija and more — in a single model.","Word-level and segment-level timestamps, ready for subtitle generation.","No per-minute billing and no data leaving your VPS.","Model choice via ASR_MODEL env var: tiny, base, small, medium, large-v3.",[24,27,30],{"title":25,"description":26},"Meeting and interview transcription","Send confidential meeting recordings directly to your private endpoint and get timestamped text back. No HR or legal data ever leaves your infrastructure.",{"title":28,"description":29},"Podcast and media subtitling","Process audio uploads server-side and receive SRT subtitle files. Plug the endpoint into your CMS or media pipeline to automate subtitle generation at zero marginal cost.",{"title":31,"description":32},"Voice-to-text for internal tools","Integrate the REST API into your CRM, support ticketing or note-taking tools. Let agents dictate, let the API transcribe — at fixed monthly cost instead of per-minute billing.",[34,37,40,43,46],{"title":35,"body":36},"Deploy from the Marketplace","Open the ServOrbit dashboard, go to Marketplace → Artificial Intelligence → Whisper, and click Deploy. Docker pulls the image and starts the container in under two minutes. The first start also downloads the ASR model weights (~270 MB for base); the download is cached so subsequent restarts are instant.",{"title":38,"body":39},"Access the API","After installation, use the address shown in your client area. The Swagger UI is available at `\u002Fdocs` for interactive testing. The main endpoint is `POST \u002Fasr`: attach your audio file and set the `output` parameter to `txt`, `json`, `srt`, `vtt` or `tsv` according to the format you need.",{"title":41,"body":42},"Transcribe your first file","From a terminal or your application, send a request:\n```\ncurl -F \"audio_file=@recording.mp3\" \"https:\u002F\u002Fyour-address\u002Fasr?output=txt\"\n```\nYou will receive the full transcription as plain text. For timestamped segments add `output=json`.",{"title":44,"body":45},"Change the model if needed","The default model is `base` (fast, ~140 MB). To improve accuracy, switch to `small` (better for noisy audio, ~500 MB) by updating the `ASR_MODEL` environment variable. A VPS with 2 GB of RAM handles `small` comfortably. Contact support if you want to resize your VPS.",{"title":47,"body":48},"Integrate into your pipeline","The endpoint is OpenAI Whisper-compatible: any library or tool that can call the OpenAI transcription API can be pointed at your private endpoint instead. Update the base URL and remove any API key — authentication is handled at the reverse proxy level by ServOrbit.",[50,53,56,59,62],{"q":51,"a":52},"Which languages does Whisper transcribe?","The model recognises 99 languages including Arabic, French, English, Spanish, Darija and many more. Transcription and translation to English are handled by the same model, selected via the `task` parameter (transcribe or translate).",{"q":54,"a":55},"Which model should I choose for a 1 GB VPS?","The `base` model (default) runs comfortably on 1 GB of RAM and 1 vCPU. It delivers solid accuracy for clear speech. For noisy recordings or lower-resource languages, `small` is a better fit and works well on a 2 GB VPS. The `large-v3` model requires 8 GB of RAM and is recommended for GPU VPS plans.",{"q":57,"a":58},"Is there a web interface to upload files?","Whisper is deployed as a REST API with a Swagger UI at `\u002Fdocs` for interactive testing. It does not include a standalone file upload web app. You can call the API from your own interface, from tools such as n8n or Make, or directly from the command line with curl.",{"q":60,"a":61},"Can I use it as a drop-in for the OpenAI Whisper API?","Yes. The endpoint is OpenAI-compatible: any library or integration that targets the OpenAI transcription API can be redirected to your private instance simply by changing the base URL. No API key is required on the server side — access is managed by the reverse proxy.",{"q":63,"a":64},"Do my audio files leave the VPS?","No. The audio is processed entirely locally on your VPS. No data is sent to OpenAI or any third party. Files are kept in memory during processing and are not stored on disk after the transcription is returned.",{"version":66,"license":67,"ram":68,"cpu":69,"disk":70},"faster-whisper \u002F CTranslate2","MIT","1 GB minimum (base model), 2 GB recommended (small model)","1 vCPU","5 GB minimum (model cache)",[],[73,82],{"name":74,"slug":75,"categorySlug":76,"categoryName":77,"categoryColor":78,"logo":79,"tagline":80,"description":81},"Open WebUI","open-webui","ia","Artificial Intelligence","text-purple-400 bg-purple-500\u002F10","https:\u002F\u002Fcdn.jsdelivr.net\u002Fgh\u002Fselfhst\u002Ficons\u002Fsvg\u002Fopen-webui.svg","Web interface for your LLMs — Ollama, OpenAI, Mistral — hosted on your own server.","Web interface to interact with your local or remote LLMs. Your data stays on your infrastructure — no third party involved.",{"name":83,"slug":84,"categorySlug":76,"categoryName":77,"categoryColor":78,"logo":85,"tagline":86,"description":87},"Dify","dify","https:\u002F\u002Fcdn.jsdelivr.net\u002Fgh\u002Fselfhst\u002Ficons\u002Fsvg\u002Fdify.svg","Build LLM applications with drag-and-drop — chatbots, agents, RAG pipelines — no backend required.","Build LLM applications visually: chatbots, RAG agents, pipelines — without writing any backend code.",[89,90],"heberger-open-webui","heberger-ollama-vps",{"key":76,"slug":76,"name":77,"objective":92,"icon":93,"color":78},"Build, host and run AI solutions.","ai",1786485885135]